Verifying bin content in an automated materials handling facility
    16.
    发明授权
    Verifying bin content in an automated materials handling facility 有权
    在自动化材料处理设施中验证垃圾桶内容

    公开(公告)号:US09120621B1

    公开(公告)日:2015-09-01

    申请号:US14225326

    申请日:2014-03-25

    CPC classification number: G06K9/00771 G05D2201/0216 G06K9/00671 G06Q10/087

    Abstract: This disclosure describes a device and system for verifying the content of items in a bin of an inventory holder within a materials handling facility. In some implementations, a bin content verification apparatus may be positioned within the materials handling facility and configured to capture images of inventory holders that include bins as the inventory holders are moved past the apparatus by mobile drive units. The images may be processed to determine whether the content included in the bins has changed since the last time images of the bins were captured. A determination may also be made as to whether a change to the bin content was expected and, if so, if the determined change corresponds with the expected change.

    Abstract translation: 本公开描述了用于验证材料处理设施内的库存持有者的仓中的物品的内容的装置和系统。 在一些实施方式中,垃圾箱内容验证装置可以位于材料处理设施内,并且被配置为当库存持有者通过移动驱动单元移动通过设备时,捕获包括仓的库存持有者的图像。 可以处理图像以确定包含在箱中的内容自从捕获箱的最后一次图像以来是否已经改变。 还可以确定是否预期对箱子内容的改变,如果是,则确定的更改是否与预期的变化相对应。

    Cluster-trained machine learning for image processing

    公开(公告)号:US09704054B1

    公开(公告)日:2017-07-11

    申请号:US14870575

    申请日:2015-09-30

    CPC classification number: G06K9/46 G06K9/4628 G06K9/6218 G06K9/6267 G06K9/6281

    Abstract: Image classification and related imaging tasks performed using machine learning tools may be accelerated by using one or more of such tools to associate an image with a cluster of such labels or categories, and then to select one of the labels or categories of the cluster as associated with the image. The clusters of labels or categories may comprise labels that are mutually confused for one another, e.g., two or more labels or categories that have been identified as associated with a single image. By defining clusters of labels or categories, and configuring a machine learning tool to associate an image with one of the clusters, processes for identifying labels or categories associated with images may be accelerated because computations associated with labels or categories not included in the cluster may be omitted.

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